Load data
library(dplyr)
library(readxl)
library(Seurat)
library(ggplot2)
library(ggsignif)
source('../scripts/helpers.R')
li <- readRDS('~/Dropbox (Brickman Dropbox)/sc_seq_analysis/Blacky/services/scRNAviz/data/li_et_al_2020_endoderm.rds')
Idents(li) <- li@meta.data$Population
fung <- readRDS('../data/processed/01_fung.filtered.RDS')
fung <- NormalizeData(fung)
fung <- ScaleData(fung)
Idents(fung) <- fung@meta.data$Stage
fung <- fung[, fung$Condition %in% c('ADE_111_1213', 'VFG83_1025')]
xls_genes <- read_excel('../data/Gene_list_for_violin_in_vitro_in_vivo_260221.xlsx')$Gene_list_for_violin_in_vitro_in_vivo_260221
common_genes <- intersect(rownames(fung), rownames(li))
genes <- intersect(xls_genes, common_genes)
print('Missing genes from the list')
## [1] "Missing genes from the list"
print(setdiff(xls_genes, genes))
## [1] "POU5F1" "GAT6" "HNF1B" "LHX1" "CD133" "ID3" "ALB"
## [8] "NKX6-1" "SERPINA1"
